I. Overview
We are seeking an experienced and highly specialized Digital Marketing Data Architect to lead the design and implementation of Enterprise Data Warehouse (EDW) data model, with a critical focus on integrating and utilizing data from Adobe Analytics and other core digital marketing systems.
This role is essential for transforming raw digital interaction data into a unified, campaign-ready data model that will directly power customer segmentation, campaign management, and marketing effectiveness reporting. The ideal candidate is a hybrid professional with strong data architecture skills and deep expertise in digital marketing principles and Adobe data collection nuances.
II. Key Responsibilities
Architecture & Modeling
- Adobe Analytics Data Modeling: Act as the Subject Matter Expert (SME) to design, validate, and enhance the conceptual, logical, and physical data models for all Adobe Analytics data feeds (including Data Warehouse and/or Data Feeds).
- Campaign Data Integration: Architect the integration of data from various sources including Adobe Analytics, Sitecore (Content Management), and ECID (Experience Cloud Identity Service) into the EDW to create a unified Customer 360 view for campaign use.
- Documentation & Validation: Lead the review, validation, and enhancement of existing data model, Business Requirements Document (BRD), and System Design Architecture (SDA) documents to ensure alignment with current marketing campaign objectives.
- Data Governance: Define standards and best practices for data quality, data lineage, metadata management, and data usage policies for all marketing and campaign data within the EDW.
- Campaign Enablement: Design data structures that support advanced marketing use cases such as audience segmentation, personalization, campaign attribution, and lift analysis.
- Channel and Tagging Expertise: Advise on the proper mapping and modeling of key digital marketing concepts, including UTM Tags, search engine data, social media interaction data, and other channel-specific tracking parameters.
- SEO/Digital Insights: Ensure the data model captures the necessary granularity to support analysis on Search Engine Optimization (SEO) performance and the effectiveness of different marketing channels.
- Sitecore & ECID: Ensure data integration from Sitecore is correctly mapped to customer profiles using the ECID to achieve a persistent, cross-channel customer identity.
- Collaborate closely with Data Engineers on ETL/ELT pipeline design, ensuring efficient and accurate data ingestion and transformation from source systems to the target EDW model.
- Work with Marketing/Campaign Managers and Business Analysts to translate high-level campaign requirements into technical data specifications.
- Provide technical leadership and mentorship on digital marketing data practices to the broader data and analytics teams.
Technical Expertise
- 8+ years of experience as a Data Architect, Data Modeler, or a similar role focused on Enterprise Data Warehousing.
- Deep, hands-on expertise with Adobe Analytics (specifically its data export/data feed structure, eVars, props, and event data).
- Note: Experience modeling Adobe Analytics data for an external data warehouse is highly critical.
- Extensive knowledge of Digital Marketing/Campaign Management concepts (e.g., attribution models, conversion funnels, A/B testing data, customer journey analysis).
- Thorough understanding of digital tracking standards, including UTM parameters, cookie/identity management, and the difference between session, visitor, and hit data.
- Familiarity with the types of data generated by and collected from social media platforms and how to model that data for campaign effectiveness.
- Excellent communication skills with the ability to bridge the gap between technical teams and non-technical marketing stakeholders.
- Proven ability to lead technical design sessions, challenge existing assumptions, and drive consensus on data architecture decisions.
- Exceptional analytical and problem-solving skills to troubleshoot complex data integration and modeling challenges.